{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "% matplotlib inline\n",
    "\n",
    "import sys\n",
    "sys.path.append('../../')\n",
    "import logomaker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zWCdYvTfVVJ5A8rP/ncVE3m41NdnXlVvQ98Tlx39HmwiEqiAEkgL9+mLpdhFc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\n0REhr1HJ0Vj3Wr2iubHGWlly85JzGmPJtSU8uO1B7nzoToovL8YvJz8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uR2q70JgtDK77\nFI+0WPlCaz7auScGOhqheqCGn5f/klxbDo/X/ZMudzdRcQsRMf/OL15wcP9ftuEPBPB5fJRuLMXv\n9+N0OPG5fezo3MX3Dz3Iod4yXm/eBIA+Lh5TWiZCo6HlxadRqdRs3vw9TEN/xzNwgObmvbT1OHnw\nH7v4+xvl/OrZUjbtqRsdz7DHx6a99aOv23qc/HXDEXz+8eMR6Ew6ViQs45DjCO92vMe86DkY1QZU\nQs1NaTfww8M/HVWzq4Wa/yp+gCfq/olVa6Gzs5J33/0FZnMsublXkpa2BJd0Me8PC1j+zRXssx6k\n+NZZZFjSuTJJCXTTOtxGWV85w8FMg/OiZrMsfikJBkVbYtKf6EcfWAEFPyii/ZIucr6biy/go//w\nfgYrjzJ4rJyEKxRtjtc7jNd7bkI/LOgvAk7ao7/iDNUvaJYuTeW663JZsSKd228vnjDdq0qllJ9N\n0JIPOyq1hkDQBSspZz45c644JTJdKBqtnpnLbiciLp3EzLmkFywnLs6EVquiulqxUq6tdTA05EVz\nsv/WRxQhxFXA61LKz0kpf3jGE86CqmYHgeC+SIdDuXG7XH0nPAN0JHfR+d0+9s85zEu5r2G0m3Ab\nTSyYcS3/W/sox/oqUAtFWhi0ymp+JDLesN9FjjWbosgCrBpFOzXLWc0V9gDzbW4K4w0Mub387t23\nmD/PQkaRn62Vx/H4/Dy9pZKnt1RSXteN2+PD6RuifbiDL++5D5PaSITWRtuReg789Cnumx3L1TZw\nOpyYr7Qy4/kCtuXvZOg6NzqTjkGfk8sSVvK9gz/EG1B+k4/caGTLFTH88wvZvFLiodfVy8xV99Ge\nlo0oXMFwUhaJ0WZe21XLKzuqWTMvjT0VY8ZxOrWKlLjxIzSeTGJ2IpZICy83bSBWH8PVyVfwaI1i\nYOvpN/Pemyo+H/td4gMZAPgDfqJ10Xwx97NohQa93opGowcETzxxC9XVb+FSu6kx1jFkHqZUfYBm\n0cqOzl18IutOVsYrwXP6PH1sbnub31X+iecbX2LQOzgavvdTlw1ww/whYq3KJG39guspN1Xwrn87\nqxIvRROcpAdcLto2vEDX1jfxel10dJTT3Lxvsj+zcbk4/r1hkFL6gU4p5dUf9FimEyEEJSVJrFqV\nicEw8c7UiHGZ2z1mld7R4bygBb9Ob8Y9PGaMODTQjct5+tgAtphk5q66h/yF16NSa1CrVcyYEcNb\nb9WyfXsjr71WRUKC+YLSdJwjq4AfCiF+OdV+9P7AqcYPWq0p+DyW0THJaOf2hE8yVDaTVeb1WLRm\nPEfclP/2CF+XXyb5QOJoGFy9VvGhH1kl9rp7yTZn0u/pp2qgGikliWVvkVKzi4xND1NsdqFSgcbg\np32wn8R4AxazGjHYT+4bfyKyqRzNpqdQuZw4fU5+Mve/uSPjY7zesomKgSrcsS4st1tw5gziSOtC\nJQQOjwO7wc7sqFmoUCGEwLa7iqTNR/ip/2PM8iqaheXbF9PzUCe3a26huKGAKEMUywtvYy9tHB+o\nZlGsEsRqZG7ucLq5ffWYRb1arWJ5sbLf39U3TP+gh09dM5P69gE6HUOjaXR7mnuYf40SYnmev4Ss\ntgW88YSN+AbFdda0Zwjju0dIcOjx7Vdc+B6rfZK/1/wDIVT0eBzYbHbuuOMZpPRjt8+hsHAdUZpY\nPHtXcv9PariWrzDLOpcB7wD1zga+PfOb6FV6LBoLUboovjPzW+hVev5e8wTtrg4AEiP9xFoDo/YU\nLza+QqophetSruYvx/8GQOklqyhbvpqaL93PVqFmaKibQMDH8HAPfv/ZxV4IJSzoLy6mJszSRwCz\nWYtaLejuHvOH3bjxODU1vR/gqM4NgzmSQcdYGM7mql201U7sxjQRK1akj8YV6OoaYsWKibUCHzWk\nlN8Aviil/JqU8mtT2bZlnDSv2dmruO6637Bgwb+NjaFbT92eQSIDZvZu8+Lx+dH0qOk82IG3x8PA\n4f5RoWbUSfTasQlER+8wze1uLOpI2vqUNMHevj5UOh2+/j68jh60ajVXZc1ne2U9y9JzmZ+SSb9e\n0nDPev414yB1V86mS+0iQmuj3tlApj6X7xd/l+LIIlweN4m+BAwqA539XWhNWtwBDzq1lsr+Krrd\nPbj9buLdBpwDPQzt24eoqAEgeuks0m68kqfe60GXmAHAoDNA9RNrqXvn1MiUv362lCz7iQZ5t1ya\nq5w37OVXz5WiUinpsQ06DcP9wxStKMIcaWbVJ1Yp9fa/jG7b/+M76dVkDr+HlJIVd6yka14R/7ev\nhVlXKL78a+1rWBS3kJeaXmV/zwEcHgePDO/Cm1FM6YwMjohe1F4XN23/LQ+V+Mnb/TxGoSwKNjRv\npM/bR6w+hqLIAnReG/urOphrWsoDaT8mWhvLuw1+HnjTQ1VPgKeO+PD4Jem+uRx4Kxo6UskTiwF4\n2+Vhm8vD6wOD7PT6UanGtuYm0k5OhrAx3sXFpH4pQohc4NvAi1LKaXMx+iARQhAfb6a+vo/i4gRc\nLh/19Q6WLr1wYt6fjDUqiZbqvbiH+tHqzXQ1HyM5Z+GZTzyJxEQLd945iwMH2sjOjqKo6CPhG382\nfFUI4QaYSmGfnRTBP75zFTaTjiG3j6QYM3FxVuLi8k6o52hto+qxTSy9ZymqbccY6FYMKluPt+J1\nebFGW/G4POiAK2YNnXDulapZ/HJLDUsyo7l71Uy80surX55FcWQW78wvYlFsJzdKLwORR1mUnEmb\nqpxmj5YMXTpVO9xE6BeTZo3FEBVBYWQCgd44PvfQZm69NI+VN4JGCoZUg5iFDgM6/OoAM6zZbG1/\nD0/Aw9zo2WhVWraUqAgEkvH5/bS4j/EDwNPQTl1zPwvjLMQHfAR8Pip/8FV+N7cIbethOitjiMsd\ni0B304oThX+onOt3urlmcSZ6jZpoqwGdRoV6eSptCcNkZsXx4Jtv8MAVVyKy57O7y0BxcjEz0hMQ\nQnDgyaf4uEVS7vJSvrOUuSsWUGiZSWOzm5zua/nsnLXoNILiyCLqnQ3k23KxaC1Ijxeh0RDLEI76\narz9DuwmO3ZjIi81beC+wv9Aq9JSEpvNO2/38/TeTr512wJ0GjWLk1X8YoeXr2/y8OdrdejUAlVk\nDyuXWehzt5BkVcynrre8R29vHTNmrAUc6HTK9otWazpB6J8tYUEf5hSklJVCiEeAcS3ZhBCfAT5z\nXgc1DWRlRbFrVzPp6RFUV/cSCEjs9gvH6v5kou3KjXH/239DqzPhHurHdopf/eTIyIgkI2N8Q8aL\ngG1SyienulG9TjOaaS0Ut9dPfXs/kWY98VEmIlIEeV+2MhDbRvo9NoxRBrKWz+SmR77GXzcf47LZ\nmRitJuiBBdmeE/voqOcSTTvamgY8BZFYI4pY6r2D//v7ET555b8zLyoBlQcyHj9CRJHA5lRh0Osg\nNUBOXz0yMZ3GnQdIT0uj0zHEnmNtXLUwk6fequCutYWkdfSi3buXGJ2JmPZuDAE1+l7I6s5iX8MA\n3WleRJzgksGFNHU7eWJ7I3esUlarB/UuBmICDGf6OSgdZKgzsC5fxntSS6bZRIbNHHIlYlRtX93i\nCD6P2THExerQmr1ERWnYUVfN/Px4Wvv7efZAKbEWC88cKOUH116H71grhceaSY+Ooq+hhkD6etxR\ng3gCkKQfZkhzHFhA5ZMNeDv7mLe8mNKt5Sy9vBiTNBGQAQ70HmJFzDKGdAGO3jSLuJQIuuMyMfg6\nyLDks/mQmyx7BG6vCZfFR9f+vSx567esv+4mGv74E+Lv/wEOp5qVyXrqB3x0OrREG/xkNHnZtaOP\nXq+KeTcp/1MRfRXdQy1cVnALASnR6y185zvtCHFuyvewoL+4+N/xCoUQl3KiWn/ceiNIKf8M/Dl4\n7gXrdV1SksTOnU0899xRAAoKYjGbP1yBcc4Grd5Iat5S6su34qIXa3QSEbFpH/SwLkRuEEIsAXxT\nuaL3+gK0dA9iNmhRqxR1c89gJ6/vepeMmEw297ewbvZC0Fvo9EVhc8WRGgFaoWV//z7KZB3rbknk\neM9hhBg/HG2ttONPtNEVENQ6jcwkgC6pmaJZcNxZSap0EWPIY+/sq2jtdnLtkiyyYm14NJKjydkI\nr57s4igcfjcDHhe7Bveyak4Wcw0+vLhpz7VRdXcxNRE65FA0drwEyirR7d/P9TmZWHuUfeTO3gMw\nPMjdi3WoxVGggMvnJ/NaxV48Og8rspSEO3vj0nEN+OhJS6bBL4jtcRIISHoHXDhdXuWzUqv41u0L\n0IYYhDoGXXS4HKCKJzpajcvjIxAIEG0yY9TpiDGZGfZ68S4pZI/PRKXWwJLVNlRqFfVJWdR19FOU\nH4ElaBuh0kjc8ZFE9HdhSU1CIOh9pJ+ISAuXJq1m0OcieYGZtPQbOVzVR48zmmsi8zCoAyyxa9h0\nrInogji0mgQ6Y+w8tXgda+25VBuszBEqSmv1/O8zsfz41h5q2iS5CUPscvlp18DKxYkc6m5iSUoq\n0YkziXCms7nsGNmxdnLiE08IIfx+CQv6iwgp5bj5Q6WUW4AtI6+FEInAdwGjEGK/lLJ+vPMudKKj\njVx3XR6vvVZFTIyRq6++cDLYTUTGzMswmCMZHuwlJXfxOe3rXYwIIZKBH0+i3jzgRpRAVP8ppRw/\nFmwIWo2KHfuPsrd6gHWLk1k0Mwu90OAfduEMDJKsF5j0Rjpbh3Ef15NUHE1bdR/uJC9pg1r6Kj1E\nJftZZk5AIjnSMMQjhwWFsZL5SVCcaqJRP0yTapgZmVG0iSFmCzXOsiYSjf0UJGRh6lPhNrvIiCgj\nLdlA/1AnvX1Z2Ey5xHj7SE6Mob6tlcG4OCwmwTKDhiSflhWpOjQ+iVmdQ03zIFEuSaqpCL3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t2ck+96L8icZjzBPgO4U6nvJVUQckstiF6aZ3x0zn2qGnYgyVRISi2SQovKdBBJAsFjByBy2Szi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\nhBBCdGKS6IUQQohO7P8B5MJDeJgH2xoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x324 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set default styling \n",
    "fontsize=6\n",
    "mpl.rcParams['font.size'] = fontsize\n",
    "mpl.rcParams['text.usetex'] = False\n",
    "\n",
    "# create figure and gridspec\n",
    "fig = plt.figure(figsize=(7, 4.5))\n",
    "gs = gridspec.GridSpec(nrows=4, ncols=5)\n",
    "\n",
    "###############################################\n",
    "### CRP logo\n",
    "ax = fig.add_subplot(gs[1, 1:3])\n",
    "\n",
    "# load crp energy matrix\n",
    "crp_df = -logomaker.get_example_matrix('crp_energy_matrix',\n",
    "                                        print_description=False)\n",
    "\n",
    "# create Logo object\n",
    "crp_logo = logomaker.Logo(crp_df,\n",
    "                          ax=ax,\n",
    "                          shade_below=.5,\n",
    "                          fade_below=.5,\n",
    "                          font_name='Arial Rounded MT Bold')\n",
    "\n",
    "# style using Logo methods\n",
    "crp_logo.style_spines(visible=False)\n",
    "crp_logo.style_spines(spines=['left', 'bottom'], visible=True)\n",
    "crp_logo.style_xticks(rotation=90, fmt='%d', anchor=0)\n",
    "\n",
    "# style using Axes methods\n",
    "crp_logo.ax.set_ylabel(\"$-\\Delta \\Delta G$ (kcal/mol)\", labelpad=-1)\n",
    "crp_logo.ax.xaxis.set_ticks_position('none')\n",
    "crp_logo.ax.xaxis.set_tick_params(pad=-1)\n",
    "\n",
    "###############################################\n",
    "### 5'ss logo\n",
    "ax = fig.add_subplot(gs[0, 3:5])\n",
    "\n",
    "# load ss probability matrix\n",
    "ss_df = logomaker.get_example_matrix('ss_probability_matrix',\n",
    "                                     print_description=False)\n",
    "\n",
    "# create Logo object\n",
    "ss_logo = logomaker.Logo(ss_df,\n",
    "                         ax=ax,\n",
    "                         width=.8,\n",
    "                         vpad=.05,\n",
    "                         fade_probabilities=True,\n",
    "                         stack_order='small_on_top',\n",
    "                         color_scheme='dodgerblue',\n",
    "                         font_name='Rosewood Std')\n",
    "\n",
    "# style using Logo methods\n",
    "ss_logo.style_spines(spines=['left', 'right'], visible=False)\n",
    "\n",
    "# style using Axes methods\n",
    "ss_logo.ax.set_xticks(range(len(ss_df)))\n",
    "ss_logo.ax.set_xticklabels('%+d'%x for x in [-3, -2, -1, 1, 2, 3, 4, 5, 6])\n",
    "ss_logo.ax.set_yticks([0, .5, 1])\n",
    "ss_logo.ax.axvline(2.5, color='k', linewidth=1, linestyle=':')\n",
    "ss_logo.ax.set_ylabel('probability')\n",
    "\n",
    "###############################################\n",
    "### WW logo\n",
    "ax = fig.add_subplot(gs[1, 3:5])\n",
    "\n",
    "# load ww information matrix\n",
    "ww_df = logomaker.get_example_matrix('ww_information_matrix',\n",
    "                                     print_description=False)\n",
    "\n",
    "# create logo object\n",
    "ww_logo = logomaker.Logo(ww_df,\n",
    "                         ax=ax,\n",
    "                         font_name='Stencil Std',\n",
    "                         color_scheme='NajafabadiEtAl2017',\n",
    "                         vpad=.1,\n",
    "                         width=.8)\n",
    "\n",
    "# style using Logo methods\n",
    "ww_logo.style_xticks(anchor=0, spacing=5, rotation=45)\n",
    "ww_logo.highlight_position(p=4, color='gold', alpha=.5)\n",
    "ww_logo.highlight_position(p=26, color='gold', alpha=.5)\n",
    "\n",
    "# style using Axes methods\n",
    "ww_logo.ax.set_ylabel('information (bits)')\n",
    "ww_logo.ax.set_xlim([-1, len(ww_df)])\n",
    "\n",
    "###############################################\n",
    "### ARS logo\n",
    "ax = fig.add_subplot(gs[2, :])\n",
    "\n",
    "# load ARS enrichment matrix\n",
    "ars_df = logomaker.get_example_matrix('ars_enrichment_matrix',\n",
    "                                      print_description=False)\n",
    "\n",
    "# load wild-type ARS1 sequence\n",
    "with logomaker.open_example_datafile('ars_wt_sequence.txt',\n",
    "                                     print_description=False) as f:\n",
    "    lines = f.readlines()\n",
    "    lines = [l.strip() for l in lines if '#' not in l]\n",
    "    ars_seq = ''.join(lines)\n",
    "\n",
    "# trim matrix and sequence\n",
    "start = 10\n",
    "stop = 100\n",
    "ars_df = ars_df.iloc[start:stop, :]\n",
    "ars_df.reset_index(inplace=True, drop=True)\n",
    "ars_seq = ars_seq[start:stop]\n",
    "\n",
    "# create Logo object\n",
    "ars_logo = logomaker.Logo(ars_df,\n",
    "                          ax=ax,\n",
    "                          color_scheme='dimgray',\n",
    "                          font_name='Luxi Mono')\n",
    "\n",
    "# color wild-type ARS1 sequence within logo\n",
    "ars_logo.style_glyphs_in_sequence(sequence=ars_seq, color='darkorange')\n",
    "\n",
    "# highlight functional regions of ARS1\n",
    "ars_logo.highlight_position_range(pmin=7, pmax=22, color='lightcyan')\n",
    "ars_logo.highlight_position_range(pmin=33, pmax=40, color='honeydew')\n",
    "ars_logo.highlight_position_range(pmin=64, pmax=81, color='lavenderblush')\n",
    "\n",
    "# additional styling using Logo methods\n",
    "ars_logo.style_spines(visible=False)\n",
    "\n",
    "# style using Axes methods\n",
    "ars_logo.ax.set_ylim([-4, 4])\n",
    "ars_logo.ax.set_ylabel('$\\log_2$ enrichment', labelpad=0)\n",
    "ars_logo.ax.set_yticks([-4, -2, 0, 2, 4])\n",
    "ars_logo.ax.set_xticks([])\n",
    "\n",
    "###############################################\n",
    "### saliency logo\n",
    "ax = fig.add_subplot(gs[3, :])\n",
    "\n",
    "# load saliency matrix\n",
    "nn_df = logomaker.get_example_matrix('nn_saliency_matrix',\n",
    "                                     print_description=False)\n",
    "\n",
    "# create Logo object\n",
    "nn_logo = logomaker.Logo(nn_df, ax=ax)\n",
    "\n",
    "# style using Logo methods\n",
    "nn_logo.style_spines(visible=False)\n",
    "nn_logo.style_spines(spines=['left'], visible=True, bounds=[0, .75])\n",
    "\n",
    "# style using Axes methods\n",
    "nn_logo.ax.set_xlim([20, 115])\n",
    "nn_logo.ax.set_xticks([])\n",
    "nn_logo.ax.set_ylim([-.6, .75])\n",
    "nn_logo.ax.set_yticks([0, .75])\n",
    "nn_logo.ax.set_yticklabels(['0', '0.75'])\n",
    "nn_logo.ax.set_ylabel('             saliency', labelpad=-1)\n",
    "\n",
    "# set parameters for drawing gene\n",
    "exon_start = 55-.5\n",
    "exon_stop = 90+.5\n",
    "y = -.2\n",
    "xs = np.arange(-3, len(nn_df),10)\n",
    "ys = y*np.ones(len(xs))\n",
    "\n",
    "# draw gene\n",
    "nn_logo.ax.axhline(y, color='k', linewidth=1)\n",
    "nn_logo.ax.plot(xs, ys, marker='4', linewidth=0, markersize=5, color='k')\n",
    "nn_logo.ax.plot([exon_start, exon_stop],\n",
    "                [y, y], color='k', linewidth=5, solid_capstyle='butt')\n",
    "\n",
    "# annotate gene\n",
    "nn_logo.ax.plot(exon_start, 1.8*y, '^k', markersize=5)\n",
    "nn_logo.ax.text(20,2*y,'$U2SURP$')\n",
    "nn_logo.ax.text(exon_start, 2.5*y,'chr3:142,740,192', verticalalignment='top', horizontalalignment='center')\n",
    "\n",
    "###############################################\n",
    "### annotate and adjust figure\n",
    "\n",
    "# tighten layout\n",
    "plt.tight_layout(h_pad=1, w_pad=4, pad=2)\n",
    "\n",
    "# Add panel labels\n",
    "x1=.00\n",
    "x2=.22\n",
    "x3=.59\n",
    "\n",
    "y1=.97\n",
    "y2=.71\n",
    "y3=.48\n",
    "y4=.24\n",
    "\n",
    "kwargs = {'fontsize':8, 'horizontalalignment':'left', 'verticalalignment':'top'}\n",
    "\n",
    "plt.figtext(x1, y1,'(A)', **kwargs)\n",
    "plt.figtext(x2, y1,'(B)', **kwargs)\n",
    "plt.figtext(x3, y1,'(C)', **kwargs)\n",
    "plt.figtext(x3, y2,'(D)', **kwargs)\n",
    "plt.figtext(x1, y3,'(E)', **kwargs)\n",
    "plt.figtext(x1, y4,'(F)', **kwargs)\n",
    "\n",
    "# save a pdf\n",
    "fig.savefig('logos/figure1_logos.pdf', transparent=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       A      C      G      T\n",
      " 0  +0.18  -0.16  -0.09  +0.07\n",
      " 1  +0.29  -0.28  -0.11  +0.10\n",
      " 2  +0.28  -0.32  -0.17  +0.21\n",
      " 3  +0.23  -0.29  -0.30  +0.36\n",
      " 4  +0.06  -0.14  -0.06  +0.14\n",
      " 5  -0.29  +0.17  -0.49  +0.61\n",
      " 6  -0.18  -0.62  +0.85  -0.06\n",
      " 7  -0.03  -0.21  -0.32  +0.57\n",
      " 8  -0.44  -0.59  +1.12  -0.08\n",
      " 9  +0.63  +0.06  -0.29  -0.40\n",
      "\n",
      "25  -0.12  -0.02  -0.09  +0.23\n"
     ]
    }
   ],
   "source": [
    "### Print out CRP emat for Fig 1A\n",
    "print('       A      C      G      T')\n",
    "for i, row in crp_df.iterrows():\n",
    "    if i <= 9 or i==25:\n",
    "        line = '%2d'%i + ''.join(['  %+1.2f'%x for x in row])\n",
    "        print(line)\n",
    "    if i == 10:\n",
    "        print('')"
   ]
  }
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